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Get Started Free →Extract ecosystem-level organization patterns (symbiosis, emergence, resilience) as design templates for complex systems.
.claude/skills/yogsoth-ai-ecosystem-pattern/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 52% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 191% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 81% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 194% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 106% | 0% |
Extract ecosystem-level organization patterns (symbiosis, emergence, resilience) as design templates.
| Resource | Target | Current | % | |----------|--------|---------|---| | web-search | 25 | 0 | 0% | | web-research | 10 | 0 | 0% | | paper-overview | 25 | 0 | 0% | | paper-search | 15 | 0 | 0% | | paper-research | 5 | 0 | 0% |
Cannot exit strategy until ≥80% of each budget line is consumed OR yield targets are met with justification for remaining budget.
| Tactic | Role | |--------|------| | life-principles-application | Apply life's principles as design constraints | | analogy-extraction | Extract transferable ecosystem principles |
| SOP | Role | |-----|------| | ecosystem-pattern-extraction | Extract organization patterns from ecosystems | | evolution-mechanism-transfer | Map ecosystem dynamics to design operations | | abstraction-to-design | Abstract ecosystem patterns to design principles | | emulation-generation | Generate system designs emulating ecosystem patterns | | biomimicry-synthesis | Synthesize final output |
<!-- BEGIN available-tables (generated) -->
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use | | --- | --- | | life-principles-application | Apply life's principles as design constraints. Orchestrates ecosystem-pattern-extraction → evolution-mechanism-transfer → abstraction-to-design. |
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | abstraction-to-design | Abstract biological principle to design principle. Bridge from biology to engineering. | | biomimicry-synthesis | Synthesize all biomimicry outputs into a structured idea report. Integrate biological strategies, design principles, and technical solutions. | | ecosystem-pattern-extraction | Extract ecosystem-level organization patterns (symbiosis, emergence, cycles, resilience). | | emulation-generation | Generate technical solutions emulating biological strategies. Bridge from design principle to concrete implementation. |
<!-- END available-tables (generated) -->
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-02 | fail→fail | 22,066 | 41,832 | +90% | 1 | 1 | 0% | 3,274 | 6,830 | +109% | 0 | 0 | — |
case-01 | fail→fail | 38,436 | 39,170 | +2% | 1 | 1 | 0% | 6,196 | 6,827 | +10% | 0 | 0 | — |
case-03 | fail→fail | 31,024 | 39,484 | +27% | 1 | 1 | 0% | 4,682 | 6,826 | +46% | 0 | 0 | — |
case-04 | pass→pass | 14,445 | 28,572 | +98% | 1 | 1 | 0% | 2,090 | 4,965 | +138% | 0 | 0 | — |
case-05 | pass→pass | 21,746 | 37,534 | +73% | 1 | 1 | 0% | 3,500 | 6,819 | +95% | 0 | 0 | — |
case-06 | pass→pass | 20,302 | 34,891 | +72% | 1 | 1 | 0% | 3,400 | 6,813 | +100% | 0 | 0 | — |
case-07 | fail→pass | 30,454 | 40,553 | +33% | 1 | 1 | 0% | 4,501 | 6,836 | +52% | 0 | 0 | — |
case-08 | fail→fail | 22,667 | 31,933 | +41% | 1 | 1 | 0% | 3,889 | 5,803 | +49% | 0 | 0 | — |
case-09 | fail→pass | 15,052 | 37,589 | +150% | 1 | 1 | 0% | 2,342 | 6,823 | +191% | 0 | 0 | — |
case-10 | fail→pass | 25,245 | 43,667 | +73% | 1 | 1 | 0% | 3,771 | 6,824 | +81% | 0 | 0 | — |
case-11 | fail→fail | 16,334 | 28,267 | +73% | 1 | 1 | 0% | 2,832 | 5,461 | +93% | 0 | 0 | — |
case-12 | fail→fail | 21,818 | 35,580 | +63% | 1 | 1 | 0% | 4,048 | 6,728 | +66% | 0 | 0 | — |
case-13 | fail→pass | 11,425 | 28,653 | +151% | 1 | 1 | 0% | 1,776 | 5,214 | +194% | 0 | 0 | — |
case-14 | fail→pass | 19,962 | 36,264 | +82% | 1 | 1 | 0% | 3,308 | 6,821 | +106% | 0 | 0 | — |
case-15 | fail→fail | 22,424 | 26,436 | +18% | 1 | 1 | 0% | 4,259 | 5,594 | +31% | 0 | 0 | — |
case-16 | fail→fail | 21,339 | 11,260 | -47% | 1 | 1 | 0% | 3,261 | 1,443 | -56% | 0 | 0 | — |
case-17 | fail→fail | 19,364 | 32,962 | +70% | 1 | 1 | 0% | 3,376 | 6,808 | +102% | 0 | 0 | — |
case-18 | fail→pass | 11,255 | 29,572 | +163% | 1 | 1 | 0% | 1,966 | 5,823 | +196% | 0 | 0 | — |
case-19 | fail→pass | 17,036 | 34,945 | +105% | 1 | 1 | 0% | 2,761 | 6,809 | +147% | 0 | 0 | — |
case-20 | fail→pass | 21,657 | 36,377 | +68% | 1 | 1 | 0% | 3,332 | 6,807 | +104% | 0 | 0 | — |
case-21 | fail→fail | 23,674 | 29,725 | +26% | 1 | 1 | 0% | 4,588 | 6,201 | +35% | 0 | 0 | — |
case-22 | fail→pass | 20,307 | 27,851 | +37% | 1 | 1 | 0% | 3,808 | 5,575 | +46% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 21 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +41 percentage points is the difference between those two pass rates over the 21 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.